KUET 2022 Question Paper M.A. M.Sc. Statistics

FOR KUET EXAM PREPARATION

KUET 2022
Question Paper · M.A.
M.Sc. Statistics
EXAM YEAR TYPE SUBJECT

KUET 2022 Question Paper M.A. M.Sc. Statistics

Notes · Sample Papers · Previous Year Papers · Mock Tests

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as ag Sr. No. 133

ENTRANCF:, TEST.2O22
SCHOOL OF PHYS{CAL & MATHE,MATICAL SCIENCES
OPTION-I : STATISTICS
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OPTION-2 : MATI{EMATICS FOR STA,TISTICS
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e Minutes m Questior Booldct Se.i",
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Total Questions

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60

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Time Allowed 70 Roll No.

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Instructious for CaDdidates :
l. Write;our Enbance Tesr Ro-ll Number in rhc sprce prorldia ir'the top ofrhis n
and trtr up rhe necessary inlbrmarion rn Lhe spaces prorided on rhe Uvn arillg:ro{R:ittion sookl.t
2 ovRAirs$erShect has.an originar copy and a candidate's copy grued bcnealh it at rhe toD. whiie
mai<rng entres.rn rtre Original Copv. caididare should enswe rhalih? &;;;;i;;;;;a,eiJ6;o;ii;
so t-trat rhe entries made in rhe original copy againsi eaaliiri;;6;;;rliibF;;a rnlhE't;ri,iid"i;J.
3. A11 entries in the OMRAnswer Sheet, including answers to questions, are to be recorded in the Original
m among rhe oprions A. B. C and D and
4 rclgg:",ll."^..-"-T-":r /mosr apprgpriare response lor eachcoquestion
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pLe.cXE rglllhe appropnate response complerel} Thqinso,mplere"darkehed circle is noi

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a g response. rn no case

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not than ofoptions for any question.Aquestion with more than one darkened
rcsponse shall be considered wrons.

;. T!9r!-rri[ b€'Negati"e Markinsifc Each rrcng aqs\'r'er will lead to ihe deduction
oi u.l) marks irom the tot f ofllf"Kiaaswers.
""ore
t who woutd obtain posirive score in Entrance Test Examination shall be eligible
P*t**g8f,Bfdtdates

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9. Do not make any stray mark on the OMR shcct.

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i0, Calculators and mobiles shall not be pernitted inside the examination hall.

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et,m f?Yl,t*fff'"fhir"J,*:t hardled caretuly ir should not be folded s
aor mutirated in which
I 1 . Rough work, if any, should be done oa the blank sheets provided

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with the question

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la :1. Ensu{e that you. OMR Answer hai been signed bl,the Invigilator
be

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case

a Sheet and the candidate himself/

I4 At tbe end of lhe examinar ion. hand over the oMR Answer-i"asheei to lhe invirrldtor \ ho r^ ill jirst iear
on oMR sheer ir presence of rhe canct;aauj riina
:!:orieinal "i-"ii,."c-aia"iit c"pii"'iri"
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OPTION-I : STATISTICS
Ifthe correlation coefrcient betwe€n two va ables
1. The Bowley's coefficient of skewness ranges 5'
X and Y is 0.8, then the correlation coefficient
between :
between U X 0.4andV=Y-03is:
(A) 0andl
(A) 0.1
@) -l and 0
(B) 0.4
(C) -3 and 3
(c) 0.5
@) -1 and I
(D) 0.8
2. A manager of a departmental store wants to place
orde$ ofthe most economical size of every U.
item The law of demand states tlat the price
and

demand of commodity are inversely dated
can help him The
Which measure of central tendency
two
in aniving at the desired size ? correlation coefficient between these
economic variables would be :
(A) Arithmetic mea!
(B) Geometnc mean (A) Positive
(C) Mode @) Negative
(D) Median (C) Zero

3. If a constant is added to every item of a senes' @) Nothing definite
which one of the following measures
of
then
'1. If oi =aoi and r = 0 25, then the regression
dispersion would change ?
coefficient b*, is :
(A) Mean d€viation about mean
(A) 0.12s
(B) Range
(B) 0.0625
(C) Standard deviation
(c) 0.50
(D) Coefrcient of variation
(D) 1.00
4. Iftle geometric mean and harmonic mean of two
16' then the
numbers are respectively 28 and 8. For obtaining the regression line of X on Y :
is :
adthmetic mean ofthese two numbers
(A) E(Y - a - bX)' is minimized
(A) 4e
@) E(Y - a - bx)'? is maximized
(B) 28
(C) E(X - a - bY)'? is minimized
(c) 22
(D) EG - a - b9'? is maximized
(D) 16

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as 9. A die is loaded in such a way that an even agB are any two events, then
number 12. IfA and :
is twice as likely to occur as an odd number. IfE (A) p(A^B) = p(A) p(AlB)
(B) P(A^B)=P(A)P@iA)
:'ft:::::H"";ffi';4,1*'"""*'"'u (c) p(AuB) p(A) p(BlA) =
(o) p(AnB) = p(AlB)
'''^', 1
,
2
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13. If the moment generating finction of a random

om . co
2 .,, --.is given by M,(t) = j
c m
(B) variable X
. e
then its
; ;
m a s
;' lase l
,tandard deviation is given by :
, (A) 1/3
a g
g
(c)

4 a (B) 2/s
(c) ls
@);, (D) r/9
10. The plobability that a regularly scheduled flight 14. Let X and Y be two independent poisson variates.
departs ontime is P@) = 0.83; the probabilitythat Then the conditional distdbution of X given
it anives ontime is P(A) = 0.82; and the probability X + Y is :

Find the probability that a plane arrives on time, o
thatitdeparts andarrives ontime is p (D^A) =0.7g. (A) m poisson

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em (C) Binomial
@) Geometric
s
given tbat it departed on time :

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(A) 0.95 (D) Negative binomial
(B) 0.94 15. The density finction of a random variable X is
(c) 0.s0
given by f(x) = I "^
i{x o<x<2
(D) 0.24 tu omerwtse

The expected value of X is then :
11. In which theory of probability, the outcomes of a
equally 1'''
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random experimenl are assuned ro be

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likely ? -*.
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(B)
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(A) statisticat
s e
s em(B) Subjective la
ag
1

la (C) Classical
(c) ;

ag
@) Axiomatic (o)1

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16. The mean of a binomial distribution is 20 and its 20 For gamma distribution with single parameter :
standard deviation is 4. Then the number of trials (A) Mean > variance
is:
(B) Mean < vadance
(A) 75
(C) Mean = variance
(B) 100
(D) Mean = standard devialion
(c) 150
21 The probability distribution of a statistic
(D) 2oo
called :
17. In an exponential distributio[ with mean other than
(A). Statistic
u41ty :

(A) Mean = (vatiance)'
(B) Standard enor
(C) Frequency distxibution
@) Mean = 2 variaoce
(C) Mean = standard deviation (D) Sampling distribution
(D) Mean= variance 22. Let X - CXI,4,...,X") be a sample and (]) be tl
critical region. The power oftest is defined by :
18. Let Y have uniform distribution over the interval
(ct, P), then its mean is given bY : (n) P@ e orlH)
... B+d (B) P@ e orlH,)
IA) T (c) P(x e olHo)
p-d (D) PG e @lH,)
(B)
2
23. A company manufacturing electric bulbs clair
that the average life of its bulbs is 1600 hou
(c) P+([
12 The average life and standard deviation ol
random sample of 1 00 such bulbs were 1570 hor
.^.0-e)'
\U) -T and 120 hours respectively, then standard erlor
the average life ofbulbs is :
I 9. If X - N(p, o'?), then moment generating ftmction

ofa standard normal variate is :
(A) 12 hous

(A) @) 1.2 horus
"t'n (C) 157 hours
@) eled'r/'1
(D) 15.7 hours
(C) eir."\'/'?
(D)
"ir'"""2
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co m .
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as 24. The standard deviation ofthe sampling dishibution
28. ag
The degree ofAeedom for paired t_test based
on n
of a statistic is known as :
pairs of observations is :
(A) Standard enor (A) n-2
(B) Mean squared erlor @) z(n - l)
(c) n- I
I (C) Variance

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(D) 2n- 1

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(D) Coemcieflt of variation

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29. Comparcd to complete enumeration, sampling

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athibutes A and B: .
may

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25. Consider the 2x2 contingency

em
be unable to provide :

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(A) Reduction in cost
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A'laA:
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(B) Increase in administrative eficiency a
Bra l0 20 (C) Estimator ofenor
B, 30 40 @) Measurement of the whole populaton
30. In SRSWO\ the V(N-y) is given by :
The value of 26, for testing the independence
of
attributes A atrd B is : (A) fN-n)",
("N1"
(A) 0.8s

om Nrxrls,
I

.c
(8) 0.83 (B)
\n,/
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las
(c) o.sl
-n

ag
(c) ^,,l,N )s,
@) o.7e
I

The range ofF-variate is : /N-n\ -
(A) -o to co
@) ol ls' *
(B) 0toco 3l' The total number of possible samples of size n
from a populalion ofsize N in case of SRSWOR
(c) oto I is:

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(D) -l to 1

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c.(A)o Z test
(A)

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27. Goodness offit ofa diskibutio[ is tested
by

s
:

em (B) F rest la
(B) N,

las a g
ag (C) t-rest
(c) rNT
I;J
I
@) Chi*quare test (D)
N"

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The criterion, which enables us to classify variou
32. The differenc€ between a sample esdmate and the
36'

population parameter ftom a complete count is sampling units into different strata, is termed as

termed as :
(A) lnflation factor
(A) Human enor
(B) Sampling factor
(B) Sampling enor
(C) Sampling ftaction
(C) Non-sampling error
(D) Mistakes (D) Statirying factor
33. Stratified sampling is appropriat€ *n"n tn" ,r. If G is the grand total, T is the mrmber oftreatnentr
population is :
and N is the total number of observations, then
(A) Heterogeneous tlre coraection factor is given bY :

@) Homogeneous
(C) Finite (A) Nr
(D) lnfinite
G
34. In systematic sampling, the population is 200 and @)N
the selected sample size is 50, then the sampling
interval is i
(c) G2
*
(A) 0.2s
(B) 40
(c) 4 -I -=
(D)

(D) 2s0
38. In which of the following designs is principle of
35. A poputation of 108 units is divided into thee local control not used ?
strata whose sizes are 24,36 and 48 respectively
In proportion allocation, the number of units (A) cRD
selected ftom the second statum when sample
siz€
(B) RBD
is 18, will be :
(c) LSD
(A) 4
@)6 @) BIBD
(c) 8
(D) e
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co m .
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as 39. hone wayclassification, the test statistic ag
F is given 43. For ma\imization Lp model,
by: the simplex method
ls terminated when all values
:

Treatrnent sum of squtues (A) Cj_zj> 0
{Ai' t rror sum of sq uares
(B) cj-zj=o
Ttlah"nt."-.o- of .quu."s
m
1g, (c) zj<o
co
rnormean surn of squares

Enor mean sum ofom .
(D) cj_4<0
.c oirqu*I e m
T..ut ent rn.unm.urn
a s
squares

e
(c) 44. A solution which can indefioitely
s g l is
increase or

a
Raw su,l of squares a
decrease the value of the

, otalag of
objective f,uction
called
lD) I sum
:

squares
(A) Degenerate solution
40. Local conhol is used to :
(B) Feasible solution
(A) Reduce the eror variance
(C) Unbounded solution
(B) Reduce the number ofreplications
(D) Optimal solution
(C) Reduce the degree offieedonr

o m
45. The tend of annual production
c
(D) Decrease the number ofplots
.
ofa cornpany is

em Origin 1988; X_unit = I year; l_umt
described by the following
41. A feasible solution to an Lp problem equation yc = g+0.6X.

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(A) Must satis$ all the probiems = arurual
a
constraints production. The montl y
simultaneously trcnd equation is :
(B) Must optimize the value (A) Yc= 1.50 + 0.0041X
of rhe objective
firnction (B) Yc = 0.01 + 0.05x
(C) \-eed aot to satis& all conshainB, (c) Yc=1.80+0.06x
oqty some
ofthem
(D) Yc=1.50+0.05X
(D) Must be a comer point ofthe

m ofseasonal
feasible region

o
46. Which ofthe following is an example

.c
42. Vr'hile solving Lp problem graphicall,

o m
the area

c m
variation ?

(A). Infeasible region e
bounded by the constraints

s
is knotvn as :

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e(B) Feasible region la
(A) Recovery in business
s
la (C) Unbounded ag
g
(B) Death rate decreased due to
a
advance in
science
region
@) Critical region (c) Sudden causes by war
(D) Sale of ice cream increases
during summer

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\

is taken into consideraton
is : 52. Mortality experience
time series model wheo defining
I
4?. The multiptioative
(A) Y=T+S+C+I (A) Crude birth mto
S xC xl (B) General fertild$$re
@) Y=Tx
(C) Y = a+bx (C) Gross reploductio4@
tate
(O) Y = a+bX+ c)P (D) Net reproduction
'boredom We
index number arm-.,
of oalculatiug the 53. Computer is ftee.fto-mtiresome
+g. Firhot '"thoa
call it :
is based on :
(A) Diligence
(A) Geomeuic mean
(B) lntelligence
(B) Aritlmetic mean
(C) Earmolic mean
(c) Robotics
(D) Accutacy
(D) Quartile deviation
women ofcluld of varidios.:
ner thousand 54. Assignable causes
49. ir" "".* as natdal
oauses

bearing age
"o*
group is : (A) Arc not as impodant
and renoved
(A) Crude birth rate (B) Canbe identified
dchanc€:' caus€s
(C) Also tefcned to
as
General fertiliry
roe
(B) contxol chad
(C) Totaf fedility
mte * ** *" t*o of a in : monitorcd
of a ptooess is
(D) Gross reProdudion
rate
ss. ",
i"otor toa"o"y
indicates : (A) Raage chart
50. Na$ral inclease
(A) Higher mortalitY (B) Mcan chart
of deaths over births (C) P-ohart
@) An excess
(C) ttlgher fenilitY (D) a-chart
over deaths is carrigd out:
(D) As exc€ss ofblths 56, Process control
a8e in lndia
is : (A) Before Production
51. The chitd bearing ,
connor
(A) 15'59 Ye'$ @) After Production
(B) 20'29 Yeus (C) During Productioo
(D) A1l of&e above
G) 1549 Yeals -.
(D) 14-49 Years
ll I 8
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co m .
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as 57. I-etTt be the most emcient estimator ofe with a g
59. Let (Y' Y' yr) be a random sample
variance of and T, be any other estlmator
ofthe from a population having mean g. Let
same parameter of 0 with variance
o1. The _ (2y + 3y, +Ly.)
eficiency of T, is :
unbiased estimator ofg, then the value
(N o?1"" ofi, is :
.
m
(A) I
co
(4 oiloi
om m .
(B) 2
(c) o,lo, .c s e
e m a
(c) 3
(D) o,/o,
l a s a gl J
g where o2 is known, then 95% 60. A statistic is called sufficienl for pararneter l
(D) 4
58. If Xr-N(p,ao2)
if it a :
confidence interval for p based on a sample
ofsize (A) Possesses all three criteria of unbiasedness,
IIls: conststancy and efficiency

ta) (Xtz.oo"/J,) ile
@) Gives among all the statistics, the maximum rly
ofthe information about parameter e's
{s) (x+z.sr"/J")
m
c. o is contained in the sample
(C) Gives all iaformation about the parameter
(ct (x*r.ge"/f,n)
that
!'
em @) Gives more information about
l.to
@) (xtr.oo"/,6)
l a s the parameter

g
fv

a
than that is contained in the sample
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tn

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s em la
gla ag
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